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廣量指標

TrigosFx: Smart Money Structure & PatternsTitle: TrigosFx: Smart Money Structure & Patterns Description: This indicator is a comprehensive professional toolkit designed to automate Market Structure mapping and Advanced Pattern Recognition. It filters out market noise to help you identify high-probability setups aligned with institutional trends. By combining "Swing" Fractals with dynamic Geometry and a Multi-Timeframe Dashboard, TrigosFx allows you to trade with the confluence of Price Action and Smart Money concepts. 💎 Key Features 1. Smart Geometric Patterns (Auto-Detection) The script independently detects multiple price structures simultaneously without conflict: Channels (Purple): Identifies parallel institutional flows (Ascending/Descending). Triangles & Wedges (Blue): Detects compression and potential explosive breakouts. Rectangles (Orange): Highlights accumulation and distribution ranges. Double Tops (M) & Double Bottoms (W): Classic reversal patterns at key levels. 2. Institutional Swing Points (Fractals) Uses a "Swing" logic (default 30-bar lookback) to mark significant Structural Highs and Lows, filtering out minor internal noise to show real Support & Resistance. 3. Multi-Timeframe (MTF) Dashboard An on-screen panel that monitors the Trend Structure (Bullish/Bearish) of higher timeframes (Default: H1, H4). Strategy: Use this as a "Traffic Light". Only execute trades when the pattern breakout aligns with the higher timeframe trend colors. 4. "Smart TP" Probability Filter Intelligent Targets: Automatically calculates Take Profit levels based on pattern size. Trend Filter: If enabled, the TP label ONLY appears if the setup is aligned with the H1 Trend. Counter-trend setups are kept clean to discourage risky trades. 5. Auto-Cleanup System Keeps your charts pristine. Old or invalidated patterns are automatically deleted after a set period (default: 50 candles), ensuring you focus only on live price action. ⚙️ How to Use Analyze the Dashboard: Check the table (top-right). Is the HTF Structure (H1/H4) Bullish or Bearish? Wait for Geometry: Let the script identify a clear structure (e.g., a Blue Triangle or Purple Channel). Confirm the Breakout: LONG Setup: Price breaks UP + Dashboard is GREEN. SHORT Setup: Price breaks DOWN + Dashboard is RED. Execution: If the "TP" label appears, the probability is high. 🎨 Customization Fully Customizable: Adjust colors, line thickness, and dashboard position to fit your style. Sensitivity Control: You can tweak the lookback periods to detect faster or slower patterns. Disclaimer: This tool is for educational purposes and market analysis. Always manage your risk properly.
Pine Script®指標
由TrigosFxMentor提供
EMA20-EMA50 Separation Impulse**EMA20–EMA50 Separation Impulse Indicator** This indicator is a **trend phase classifier**, not a signal generator. It evaluates the **structural quality of a trend** by measuring the separation between the EMA20 and EMA50, **normalized by ATR**. By using volatility-adjusted distance instead of raw price or percentage, it provides a robust and comparable measure across different instruments and timeframes. ### Key characteristics * **Discrete states**, not a continuous oscillator * **Independent from price scale** (displayed in a lower panel) * **Contextual indicator**, not a timing tool * **Fully backtestable without ambiguity** ### Logic The indicator computes: ``` |EMA20 − EMA50| / ATR ``` Based on this normalized separation, each bar is classified into one of three market phases: * **Green (State 1)** Ordered trend. EMA structure is compact and stable. The EMA-based pullback setup has a statistical edge. * **Blue (State 2)** Extended trend. Separation is increasing. Edge is reduced. Trades require more selectivity or reduced position size. * **Red (State 3)** Overextended trend. EMAs are widely separated. Pullbacks to EMA20 lose effectiveness. The setup has no edge. ### How to integrate it into an EMA-based system This indicator should be used strictly as a **context filter**, not as an entry or exit trigger. Typical integration rules: * Allow long entries **only when State = 1 (Green)** * Reduce position size or require stronger confirmation when State = 2 (Blue) * Disable EMA pullback entries entirely when State = 3 (Red) Used correctly, the indicator helps distinguish **when an EMA trend-following system is operating in its optimal environment**, and when market conditions degrade its expectancy. It answers the question: > *“Is this still a healthy trend for EMA pullback trading?”* —not *“Should I buy or sell now?”*
Pine Script®指標
由danavillanueva提供
BuyLow SellHigh Bands | ProjectSyndicate________________________________________ 📊 BuyLow SellHigh (BLSH) Bands Comprehensive Trading Guide – by ProjectSyndicate ________________________________________ 🔰 1. Introduction The BuyLow SellHigh (BLSH) Bands indicator is a powerful technical analysis tool designed for the TradingView platform. Works with any symbol. Gold/FX/indices/oil/crypto/stocks. It provides traders with a clear, visual representation of: • 📈 Overbought conditions • 📉 Oversold conditions This makes it easier to identify high-probability entry and exit points. The indicator is built on: • Dynamic price channels • Fibonacci-based zones • Color-coded market structure 💡 While the BLSH Bands can be used on Forex, Crypto, and Futures, this guide focuses on Gold (XAUUSD) using: • M5 • M15 • M30 timeframes ________________________________________ 🧠 2. Core Concepts The BLSH Bands structure is created using two key components: ________________________________________ 📐 Dynamic Price Bands • Upper and lower bands are calculated using the highest high and lowest low • Based on a user-defined lookback period (fiboPeriod) • Reflects recent volatility and price range This creates a self-adjusting channel that adapts to market conditions. ________________________________________ 🧮 Fibonacci Zones The space between the bands is divided into six Fibonacci-based zones: • 0.786 • 0.618 • 0.500 • 0.382 • 0.214 ⚠️ These are not traditional retracements — they are used to grade price extremity within the channel. ________________________________________ 🎨 Color-Coded Zones Overview Zone (Fib Level) Color Market Condition Interpretation 1.000 – 0.786 🔴 Red Extreme Overbought High reversal / pullback probability 0.786 – 0.618 🟠 Orange Overbought Selling pressure building 0.618 – 0.500 🟡 Yellow Mildly Overbought Bullish momentum weakening 0.500 – 0.382 🟢 Aqua Mildly Oversold Bearish momentum weakening 0.382 – 0.214 🔵 Deep Sky Blue Oversold Strong buying interest 0.214 – 0.000 🔷 Blue Extreme Oversold High bounce / reversal probability 🖤 Solid black separator lines ensure clean visual separation between zones for precise price location. ________________________________________ 🪙 3. Trading Strategies for XAUUSD (Gold) Gold’s volatility and respect for technical levels make it ideal for BLSH Bands strategies. ________________________________________ ⚡ M5 Timeframe – Scalping Strategy Designed for fast mean-reversion trades from extreme zones. 🟢 BUY Setup • Price enters Extreme Oversold (Blue) zone • Bullish confirmation candle appears: o Hammer o Bullish engulfing • Enter BUY 🔴 SELL Setup • Price enters Extreme Overbought (Red) zone • Bearish confirmation candle appears: o Shooting star o Bearish engulfing • Enter SELL 🎯 Take Profit: • Median band (between Yellow & Aqua) 🛑 Stop Loss: • Just outside the outer band ________________________________________ 📆 M15 Timeframe – Day Trading Strategy Balanced timeframe for higher-probability reversals. 🟢 BUY Setup • Price enters Oversold (Blue / Deep Sky Blue) • Strong bullish reversal candle closes back inside bands • Enter BUY after close 🔴 SELL Setup • Price enters Overbought (Red / Orange) • Bearish reversal candle closes back inside bands • Enter SELL after close 🎯 Take Profit (Multi-Target): 1. Median band 2. Opposite extreme band 🛑 Stop Loss: • Beyond high/low of confirmation candle ________________________________________ 🔄 M30 Timeframe – Swing Trading Strategy Used for identifying major swing points. 🔍 Trend Filter • Use 100 or 200 EMA • Trade only in trend direction 🟢 Uptrend • Buy pullbacks into Oversold zones 🔴 Downtrend • Sell rallies into Overbought zones 📉 Confirmation: • Band rejection • RSI or MACD divergence 🎯 Take Profit: • Previous structure levels • Opposite band extreme 🛑 Stop Loss: • Below / above recent swing high or low ________________________________________ 🚨 4. Alerts System Alerts are disabled by default to keep charts clean. ✅ How to Enable • Open indicator settings • Check “Enable Alerts” ________________________________________ 🔔 Available Alerts 🔴 Overbought Alert • Trigger: Price crosses above 0.786 • Message: 🔴 SELL SIGNAL: Price entered Overbought Zone – Consider selling or taking profits 🟢 Oversold Alert • Trigger: Price crosses below 0.214 • Message: 🟢 BUY SIGNAL: Price entered Oversold Zone – Consider buying or entering long ________________________________________ ⏱ Alert Spacing Logic • Default: 20/50 bars • Prevents repeated alerts in choppy markets • Filters for higher-quality signals ________________________________________ ⚙️ 5. Customization Settings Adjust the indicator in the Settings panel: 🔧 Core Inputs • fiboPeriod → Band sensitivity • extremes → Price source (High/Low or Close) 🔔 Alert Controls • Enable / disable alerts • Separate control for overbought & oversold • Alert spacing (bars) ________________________________________ ⭐ How You Can Support ProjectSyndicate (3 Steps) 1. ✅ Click “Add to Favorites” to save this script to your TradingView Favorites 2. 🔎 Check out our other scripts to complete your SMC toolkit 3. 👤 Follow ProjectSyndicate for the latest updates, upgrades, and new releases ________________________________________ ⚠️ 6. Disclaimer Trading involves significant risk and may not be suitable for all traders. This indicator is a decision-support tool, not a standalone trading system. Always apply: • Proper risk management • Additional confirmations • Sound trading discipline 📉 Past performance does not guarantee future results.
Pine Script®指標
由ProjectSyndicate提供
5
MACD 12-26-9 with Slope, Convergence & Divergence1. Core Indicator: MACD (12-26-9) The script uses the standard MACD: Fast EMA: 12 Slow EMA: 26 Signal EMA: 9 It plots: MACD Line → short-term vs long-term momentum Signal Line → smoothed MACD Histogram → distance between MACD and Signal 2. Histogram Slope (Momentum Acceleration) What it is The slope measures how fast the MACD histogram is changing. histSlope = hist - hist What it tells you Positive slope → momentum accelerating Negative slope → momentum slowing Slope flip → early momentum shift (often before MACD cross) Why it matters MACD crosses are lagging. Histogram slope gives early warning of momentum changes. 3. Convergence & Divergence (MACD vs Signal) How it’s calculated The script measures the distance between the MACD and Signal lines: distance = abs(macdLine - signalLine) Convergence → distance is shrinking Divergence → distance is expanding Interpretation Convergence = compression / energy building Divergence = expansion / trend strength or exhaustion This is not price divergence, but internal momentum structure. 4. MACD Perimeter Threshold (Momentum Filter) What it is Horizontal bands above and below zero that define a “noise zone”. Inside perimeter → weak / choppy momentum Outside perimeter → strong momentum Why it’s useful Filters low-quality MACD crosses Identifies compression → expansion Helps spot trend exhaustion when momentum fades outside the band 5. Visual Encoding (What you see) Histogram colors Bright green / red → strong acceleration Dull green / maroon → weakening momentum Gray → indecision MACD line color Yellow → converging (compression) Orange → diverging (expansion) Blue → neutral Markers Up triangle → bullish convergence Down triangle → bearish divergence 6. How traders use this indicator Trend continuation MACD above zero Histogram positive Slope rising Divergence expanding ➡ Strong trend continuation Pullback entries Trend intact Histogram pulls back toward zero Slope turns up again ➡ High-probability re-entry Breakout anticipation Long convergence Histogram flattening Sudden slope expansion ➡ Breakout likely Exhaustion warning Large divergence Histogram slope weakens Momentum fails to expand ➡ Trend may stall or reverse 7. Best use cases Works best as a momentum confirmation tool Combine with: Market structure Support / resistance Moving averages Volume or Force Index
Pine Script®指標
由mattyjoy6787提供
Value Area PRO (TPO/Volume Session VAH/VAL/POC) 📌 AP Capital Value Area PRO (TPO / Volume) AP Capital Value Area PRO is a session-based value area indicator designed for Gold (XAUUSD), NASDAQ (NAS100), and other CFD instruments. It focuses on where the market has accepted price during the current session and highlights high-probability interaction zones used by professional traders. Unlike rolling lookback volume profiles, this indicator builds a true session value area and provides actionable signals around VAH, VAL, and POC. 🔹 Core Features Session-Anchored Value Area Value Area is built only during the selected session Resets cleanly at session start Levels develop during the session and can be extended forward No repainting or shifting due to lookback changes TPO or Volume Mode TPO (Time-at-Price) mode – ideal for CFDs and tick-volume data Volume mode – uses broker volume if preferred Same logic, different weighting method Fixed Price Bin Size Uses a fixed bin size (e.g. 0.10 for Gold, 0.25–0.50 for NAS100) Produces cleaner, more realistic VAH/VAL levels Avoids distorted profiles caused by dynamic bin scaling VAH / VAL / POC Levels VAH (Value Area High) VAL (Value Area Low) POC (Point of Control) (optional) Lines can be extended to act as forward reference levels 🔹 Trading Signals & Alerts Value Re-Entry Identifies false breakouts where price: Trades outside value Then closes back inside Often seen before strong mean-reversion or continuation moves. Acceptance Detects initiative activity using: Multiple consecutive closes outside value Filters out weak single-candle breaks Rejection Flags strong rejection candles: Large candle body Wick outside value Close back inside the value area These conditions are especially effective on Gold intraday. 🔹 Optional Profile Histogram Right-side volume/TPO histogram Buy/sell imbalance visualization Fully optional to reduce chart clutter and improve performance 🔹 Best Use Cases Recommended markets XAUUSD (Gold) NAS100 / US100 Other index or metal CFDs Recommended timeframes 5m, 15m, 30m Suggested settings Mode: TPO Value Area: 70% Bin size: Gold: 0.10 NAS100: 0.25 or 0.50 🔹 How Traders Use It Trade rejections at VAH / VAL Look for acceptance to confirm trend days Use re-entries to fade failed breakouts Combine with trend filters, EMA structure, or session context ⚠️ Disclaimer This indicator is provided for educational and analytical purposes only and does not constitute financial advice. Always manage risk appropriately.
Pine Script®指標
由APCapitalTrading提供
Relative Strength SpreadSPY vs IWM Relative Strength Spread Indicator The SPY vs IWM Relative Strength Spread indicator measures leadership between large-cap and small-cap equities by comparing the percent performance of SPY (S&P 500) against IWM (Russell 2000) over a user-defined lookback period. The indicator plots a zero-centered histogram in a separate pane, making relative strength shifts immediately visible. How It Works The indicator calculates the percent change of SPY and IWM over the same lookback window. It then subtracts IWM’s percent change from SPY’s percent change. The result is plotted as a histogram pinned to the 0% line. This design removes long-term drift and ensures that: Positive values indicate SPY is outperforming IWM Negative values indicate IWM is outperforming SPY How to Read the Histogram Above Zero (Green Bars) Large-cap stocks are leading → typically associated with risk-on stability and institutional flow into SPY-weighted names. Below Zero (Red Bars) Small-cap stocks are leading → often signals risk appetite expansion and speculative participation. Crosses of the Zero Line Mark potential leadership transitions between large caps and small caps. Why This Indicator Is Useful Identifies market regime shifts (risk-on vs risk-off behavior) Confirms or filters trend strength in equities Helps time rotations between large-cap and small-cap exposure Works consistently across all timeframes Because the calculation is based on percent change, the histogram remains normalized and comparable regardless of price level or timeframe. Best Use Cases As a market internals / breadth confirmation tool As a bias filter for SPY, IWM, or index futures To spot early leadership changes before price trends fully develop
Pine Script®指標
由Es-Sniper提供
The Order Flow Key LevelsThe Order Flow Key Levels — Liquidity-Based Support & Resistance The Order Flow Key Levels is a closed-source indicator that plots participation-based key levels directly on the chart as clean, horizontal lines. The goal is to help traders quickly identify key levels formed by high participation, using the interaction between price movement and executed volume. What you see on the chart The indicator draws horizontal key level lines at prices where meaningful trading activity has occurred and where price has historically shown a reaction. These lines are intended to be used as context—areas where price may pause, reject, or accept and continue. How it works (high level) At a conceptual level, the tool evaluates: Executed volume concentration at specific price levels Repeated interaction at those levels over time (participation “revisits”) Price response to participation, distinguishing between acceptance vs rejection behavior Key levels are formed from completed execution data and are designed to be non-repainting, meaning once a level is confirmed and plotted, it remains stable rather than shifting retroactively. The indicator does not predict future price direction; it provides structure and confirmation based on participation. How traders use it Treat the plotted lines as high liquidity zones Look for acceptance above/below a level as directional confirmation Use levels for entries, exits, and trade management, including defining invalidation areas beyond a level Monitor market structure as price transitions between levels (break, hold, retest, rejection) The Order Flow Key Levels is built for futures, crypto, CFDs, and other high-liquidity markets, where executed volume-based participation can provide meaningful context. While the indicator uses established price and volume concepts, it applies a proprietary methodology for identifying and filtering participation-based key levels, helping reduce noise compared to traditional support/resistance tools.
Pine Script®指標
由MasterOrderFlow提供
Smart Scalper Pro Template + VWAP 📌 Author Garry Evans Independent system developer focused on: Risk-first automation Market structure & liquidity behavior Discipline, consistency, and capital preservation “The edge isn’t the market — it’s the man who survives it.” ⚙️ Risk Management & Position Sizing The script is built around capital protection, not signal frequency. Risk logic includes: Fixed or dynamic risk per trade Market-adaptive position sizing Session-based trade limits Daily trade caps and auto-lockout protection Volatility-aware sizing (futures & crypto) ⚠️ Profit is pursued only after risk is controlled. 📊 Track Record Backtested across multiple market environments Forward-tested and actively used by the author Real-account trades are logged where platform rules allow Results vary by market, timeframe, and user-defined risk settings. 🌍 Supported Markets Designed to work across all liquid markets, including: Stocks Crypto (spot & futures) Options (signal-based framework) Futures (indices, metals, crypto futures) The system adapts to volatility and structure — it is not market-specific. ⚖️ Leverage Leverage is not required If used, leverage is fully user-controlled Risk logic scales exposure conservatively No martingale. No revenge sizing. No over-exposure logic. 🧪 Backtesting ✔ Yes Strategy logic has been backtested Filters reduce chop, noise, and forced trades Focus on drawdown control over curve-fitting 🛠 Support ✔ Yes Direct author support Ongoing improvements and updates Feature refinement based on real usage and feedback 👥 Community ✔ Yes Private user access High-quality feedback environment No public signal spam or hype-driven chat rooms ⏳ Trial Period ✔ Yes Limited trial access available Designed for evaluation only Trial users do not receive full feature access 🚫 Who This Script Is NOT For This system is not for: Traders looking for guaranteed profits Users expecting copy-paste “signal calls” Over-leveraged gamblers Those unwilling to follow risk rules Anyone seeking overnight results This is a discipline and automation tool, not a shortcut. 🧠 Final Positioning This is not a signal service. This is a risk-controlled execution framework designed to: Enforce discipline Reduce emotional trading Protect capital during bad market conditions Scale responsibly during favorable ones
Pine Script®指標
由Garrythetrader954305提供
Smart Scalper Pro Template + VWAP + FVG Invite-Only Trading Script Private Access • Risk-First • Discipline-Driven 🔐 Access Tiers Lifetime Access — $999 (Limited to 25 total seats) One-time payment Full script access All future updates included Priority support & early feature access Locked pricing — never increases Once lifetime seats are filled, this tier is permanently closed. Level 2 Access — $199 Advanced Risk & Confirmation Module Higher-confidence trade filters Enhanced risk controls & lockout logic Advanced session and volatility filters Designed for experienced, disciplined traders Reduces over-trading and low-quality setups Level 2 is feature-based, not cosmetic — it adds stricter trade qualification. Subscription Access — $99 / month Core strategy framework Risk-managed trade logic Ongoing updates while subscribed Ideal for evaluation or short-term usage Subscription does not include Level 2 advanced filters. 📌 Author Garry Evans Independent system developer focused on: Risk-first automation Market structure & liquidity behavior Discipline, consistency, and capital preservation “The edge isn’t the market — it’s the man who survives it.” ⚙️ Risk Management & Position Sizing The script is built around capital protection, not signal frequency. Risk logic includes: Fixed or dynamic risk per trade Market-adaptive position sizing Session-based trade limits Daily trade caps and auto-lockout protection Volatility-aware sizing (futures & crypto) ⚠️ Profit is pursued only after risk is controlled. 📊 Track Record Backtested across multiple market environments Forward-tested and actively used by the author Real-account trades are logged where platform rules allow Results vary by market, timeframe, and user-defined risk settings. 🌍 Supported Markets Designed to work across all liquid markets, including: Stocks Crypto (spot & futures) Options (signal-based framework) Futures (indices, metals, crypto futures) The system adapts to volatility and structure — it is not market-specific. ⚖️ Leverage Leverage is not required If used, leverage is fully user-controlled Risk logic scales exposure conservatively No martingale. No revenge sizing. No over-exposure logic. 🧪 Backtesting ✔ Yes Strategy logic has been backtested Filters reduce chop, noise, and forced trades Focus on drawdown control over curve-fitting 🛠 Support ✔ Yes Direct author support Ongoing improvements and updates Feature refinement based on real usage and feedback 👥 Community ✔ Yes Private user access High-quality feedback environment No public signal spam or hype-driven chat rooms ⏳ Trial Period ✔ Yes Limited trial access available Designed for evaluation only Trial users do not receive full feature access 🚫 Who This Script Is NOT For This system is not for: Traders looking for guaranteed profits Users expecting copy-paste “signal calls” Over-leveraged gamblers Those unwilling to follow risk rules Anyone seeking overnight results This is a discipline and automation tool, not a shortcut. 🧠 Final Positioning This is not a signal service. This is a risk-controlled execution framework designed to: Enforce discipline Reduce emotional trading Protect capital during bad market conditions Scale responsibly during favorable ones
Pine Script®指標
由Garrythetrader954305提供
BK AK-Momentum Pivot Wolf🐺 BK AK–Momentum Pivot Wolf — Momentum / Pivots / Confluence 🐺 🙏 All glory to Gd. Built with standards and discipline passed down by my mentor — thank you for the lens and the insistence on structure over noise. Update / Record A previous version of this publication was hidden due to insufficient description. This republish is a complete, self-contained explanation of what the script does, how it works, and how to use it. ✨ What this script does Pivot Wolf is a TSI-based momentum oscillator system that focuses on extremes → pivots → confirmation, then adds confluence layers (VWAP, MTF alignment, SNR, volume, regime) to reduce chop and low-quality signals. It’s built to help you: Identify momentum extremes using dynamic or static bands Detect pivot points in the oscillator at those extremes Mark divergences (regular + hidden) between price and oscillator Confirm/grade signals using a scoring system (or legacy hard filters) Visualize context via VWAP gating, MTF alignment, and regime state Project post-pivot expectation zones via T1/T2 targets Optionally enable historical learning that only applies overrides when validation is strong 🧠 How it works (high level) 1) Momentum engine (TSI blend) Computes Fast and Slow TSI. Optionally blends them using volatility weighting (ATR% normalized over a lookback) to adapt responsiveness. Smooths momentum with a Signal EMA for cross/shift confirmation. 2) Bands define “extremes” Dynamic mode uses StdDev (or robust MAD) over a lookback to size bands. Static mode uses a fixed ± level. Extremes are simply “momentum beyond the band,” with optional tolerance/smoothing. 3) Pivot detection (the main signals) Uses oscillator pivot highs/lows. A “strong” pivot is when a pivot forms outside the band (oversold/overbought). Marker styling, sizes, and tooltips are configurable. 4) Divergence logic Tracks the last two oscillator pivots and compares them to the last two price pivots: Bullish divergence: price makes a lower low while oscillator makes a higher low Bearish divergence: price makes a higher high while oscillator makes a lower high Includes hidden divergences and optional “require extreme” filtering. 5) Confluence + scoring (0–100) Instead of only hard rules, Pivot Wolf can compute bull/bear scores using: VWAP position and/or slope gating MTF direction alignment across selected timeframes Signal-to-noise ratio filter (momentum vs signal noise) Volume confirmation and regime adjustments Acceleration / deceleration behavior Structure + consolidation penalties Signals can be shown as strong or weak (optional), based on your thresholds. 6) Targets / projections After confirmed pivots, it projects expectation zones using recent run behavior: T1 = 0.618 projection T2 = 1.000 projection Targets can display continuously or only when momentum approaches. 7) Optional historical learning If enabled, it records pivot outcomes after N bars and runs a train/validation check before applying any learned overrides. If validation fails, it stays on manual settings. 🧭 How to use (simple workflow) 🧩 Check MTF dashboard for alignment (avoid fighting the stack). 🧱 Let momentum reach band extremes (OB/OS). 🔻🔺 Take pivot signals more seriously when score is strong + VWAP gate agrees. 💎 Use divergence as added weight, not as the trigger. 🎯 Manage around T1/T2 as structured expectation zones. 👁️‍🗨️ King Solomon Lens “Solomon didn’t predict. He judged. He built tests that made truth show itself. Pivot Wolf is that: pivots as boundary stones, momentum as witness, acceleration as the confession. No hammer in the Temple — rules are cut before entry. When it’s quiet, it’s saving you. When it speaks, it’s a ruling.” This is not financial advice. This is structure. If you wanted a fortune teller, you’ll hate this script. If you wanted a system that makes the market prove itself before you strike—welcome to the Wolf. 🙏 All glory to G-d—the source of all wisdom and every true edge. 🙏
Pine Script®指標
由Ki11a_B提供
Chip Distribution Pro// This source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org // Enhanced Position Cost Distribution - Auto-adaptive with improved visualization // Works with ETFs, commodities, forex, crypto, stocks - any instrument // @version=5 indicator('Chip Distribution Pro', overlay = true, max_lines_count = 500, max_bars_back = 500) //#region Inputs string GRP_GENERAL = "General Settings" int LOOKBACK = input.int(1000, 'Lookback Bars', maxval = 20000, minval = 500, step = 250, group = GRP_GENERAL) int CHART_X_OFFSET = input.int(100, 'Chart Offset', step = 10, group = GRP_GENERAL) int LABEL_X_OFFSET = CHART_X_OFFSET + 4 int CHART_MAX_WIDTH = input.int(80, 'Max Width', maxval = 500, minval = 10, step = 10, group = GRP_GENERAL) int NUM_BUCKETS = input.int(400, 'Price Buckets', maxval = 500, minval = 50, step = 50, group = GRP_GENERAL) string GRP_AUTO = "Auto-Tuning" bool AUTO_TUNE = input.bool(true, 'Enable Auto-Tuning', group = GRP_AUTO, tooltip = 'Automatically adjusts turnover rate based on volatility and volume characteristics') float MANUAL_DECAY = input.float(0.1, 'Manual Turnover Rate', minval = 0.01, maxval = 0.5, step = 0.01, group = GRP_AUTO, tooltip = 'Only used when Auto-Tuning is disabled') int VOLATILITY_PERIOD = input.int(20, 'Volatility Period', minval = 5, maxval = 100, group = GRP_AUTO) string GRP_VISUAL = "Visualization" string COLOR_SCHEME = input.string("Rainbow", "Color Scheme", options = , group = GRP_VISUAL) color PROFIT_COLOR_LIGHT = input.color(#26a69a, 'Profit Light', group = GRP_VISUAL) color PROFIT_COLOR_DARK = input.color(#004d40, 'Profit Dark', group = GRP_VISUAL) color LOSS_COLOR_LIGHT = input.color(#ef5350, 'Loss Light', group = GRP_VISUAL) color LOSS_COLOR_DARK = input.color(#b71c1c, 'Loss Dark', group = GRP_VISUAL) color CURRENT_PRICE_COLOR = input.color(color.yellow, 'Current Price', group = GRP_VISUAL) color AVG_PRICE_COLOR = input.color(#2196F3, 'Average Cost', group = GRP_VISUAL) color PEAK_COLOR = input.color(#FF9800, 'Peak Concentration', group = GRP_VISUAL) color STATS_COLOR = input.color(#434651, 'Stats Background', group = GRP_VISUAL) string GRP_LEVELS = "Key Levels" bool SHOW_SUPPORT_RESISTANCE = input.bool(true, 'Show Support/Resistance Zones', group = GRP_LEVELS) bool SHOW_PEAK = input.bool(true, 'Show Peak Concentration', group = GRP_LEVELS) float SR_THRESHOLD = input.float(0.7, 'S/R Detection Threshold', minval = 0.3, maxval = 0.95, step = 0.05, group = GRP_LEVELS, tooltip = 'Minimum concentration (relative to peak) to mark as support/resistance') string GRP_SIGNALS = "Signals Panel" bool SHOW_SIGNALS = input.bool(true, 'Show Signal Panel', group = GRP_SIGNALS) bool SHOW_KEY_LEVELS = input.bool(true, 'Show Key Price Levels', group = GRP_SIGNALS) bool SHOW_TREND_ARROW = input.bool(true, 'Show Trend Arrow', group = GRP_SIGNALS) bool SHOW_PRESSURE_BAR = input.bool(true, 'Show Pressure Bar', group = GRP_SIGNALS) // Colors for key levels color SUPPORT_COLOR = input.color(#00E676, 'Support Level', group = GRP_LEVELS) color RESISTANCE_COLOR = input.color(#FF5252, 'Resistance Level', group = GRP_LEVELS) color BREAKOUT_COLOR = input.color(#FFD600, 'Breakout Level', group = GRP_LEVELS) //#endregion //#region Candle Type type Candle int idx float hi float lo float vol float relativeVol float atrPct //#endregion //#region PCD Type type PCD array candles float minPrice float maxPrice float priceStep array lines label currentPriceLabel label avgPriceLabel label peakLabel label statsLabel label signalLabel array srZones float calculatedTurnover // New visualization elements line supportLine line resistanceLine line avgCostLine label trendArrow box pressureBar box pressureFill label pressureLabel // Create a new price label newPriceLabel(color bg, color txtColor) => label.new(0, 0, '', style = label.style_label_left, color = bg, textcolor = txtColor, size = size.small) // Create a new PCD instance newPCD() => array lns = array.new(NUM_BUCKETS) for i = 0 to NUM_BUCKETS - 1 array.set(lns, i, line.new(0, 0, 0, 0)) PCD.new( candles = array.new(0), lines = lns, currentPriceLabel = newPriceLabel(color.new(#00BCD4, 0), color.white), avgPriceLabel = newPriceLabel(AVG_PRICE_COLOR, color.white), peakLabel = newPriceLabel(PEAK_COLOR, color.white), statsLabel = label.new(0, 0, '', style = label.style_label_up, size = size.small, textalign = text.align_left, color = color.new(STATS_COLOR, 20), textcolor = color.white), signalLabel = label.new(0, 0, '', style = label.style_label_left, size = size.small, textalign = text.align_left, color = color.new(#1a1a2e, 20), textcolor = color.white), srZones = array.new(0), calculatedTurnover = 0.1, minPrice = na, maxPrice = na, priceStep = na, supportLine = line.new(0, 0, 0, 0, color = SUPPORT_COLOR, width = 2, style = line.style_dashed), resistanceLine = line.new(0, 0, 0, 0, color = RESISTANCE_COLOR, width = 2, style = line.style_dashed), avgCostLine = line.new(0, 0, 0, 0, color = AVG_PRICE_COLOR, width = 2, style = line.style_dotted), trendArrow = label.new(0, 0, '', style = label.style_label_center, size = size.large, textcolor = color.white), pressureBar = box.new(0, 0, 0, 0, bgcolor = color.new(#424242, 50), border_color = color.gray), pressureFill = box.new(0, 0, 0, 0, bgcolor = color.green, border_color = na), pressureLabel = label.new(0, 0, '', style = label.style_label_right, size = size.tiny, color = color.new(#000000, 100), textcolor = color.white)) // Auto-calculate turnover rate based on instrument characteristics calcAdaptiveTurnover(float atrPct, float volRatio) => float safeAtrPct = na(atrPct) or atrPct <= 0 ? 0.02 : atrPct float safeVolRatio = na(volRatio) or volRatio <= 0 ? 1.0 : volRatio float volBasedTurnover = math.max(0.03, math.min(0.3, safeAtrPct * 3)) float volAdjustment = math.max(0.5, math.min(2.0, safeVolRatio)) float turnover = volBasedTurnover * volAdjustment math.max(0.02, math.min(0.4, turnover)) // Store candle method method storeCandle(PCD this, int barIdx, float hiPrice, float loPrice, float volVal, float avgVol, float atrPct) => if not na(hiPrice) and not na(loPrice) and not na(volVal) and volVal > 0 float safeAvgVol = na(avgVol) or avgVol <= 0 ? volVal : avgVol float relVol = volVal / safeAvgVol float safeAtrPct = na(atrPct) ? 0.02 : atrPct bool modified = false int candleSize = array.size(this.candles) if candleSize > 0 Candle c = array.get(this.candles, candleSize - 1) if c.idx == barIdx c.hi := hiPrice c.lo := loPrice c.vol := volVal c.relativeVol := relVol c.atrPct := safeAtrPct modified := true if not modified Candle c = Candle.new(barIdx, hiPrice, loPrice, volVal, relVol, safeAtrPct) array.push(this.candles, c) this.minPrice := na(this.minPrice) ? loPrice : math.min(this.minPrice, loPrice) this.maxPrice := na(this.maxPrice) ? hiPrice : math.max(this.maxPrice, hiPrice) float priceRange = this.maxPrice - this.minPrice this.priceStep := priceRange > 0 ? priceRange / NUM_BUCKETS : 0.0001 // Get bucket index for price method getBucketIndex(PCD this, float price) => if na(this.priceStep) or this.priceStep <= 0 or na(this.minPrice) 0 else int idx = int(math.floor((price - this.minPrice) / this.priceStep)) math.max(0, math.min(idx, NUM_BUCKETS - 1)) // Get price for bucket index method getBucketedPrice(PCD this, int bucketIdx) => int safeIndex = math.max(0, math.min(bucketIdx, NUM_BUCKETS - 1)) float safeStep = na(this.priceStep) or this.priceStep <= 0 ? 0.0001 : this.priceStep float safeMin = na(this.minPrice) ? 0.0 : this.minPrice (safeIndex + 0.5) * safeStep + safeMin // Get rainbow color based on position (0.0 = bottom/red, 1.0 = top/violet) getRainbowColor(float position, float intensityRatio) => float pos = math.max(0.0, math.min(1.0, position)) int transparency = int(math.round((1.0 - intensityRatio) * 50)) // Rainbow spectrum: red -> orange -> yellow -> green -> cyan -> blue -> violet if pos < 0.166 color.new(color.from_gradient(pos, 0.0, 0.166, #FF0000, #FF7F00), transparency) else if pos < 0.333 color.new(color.from_gradient(pos, 0.166, 0.333, #FF7F00, #FFFF00), transparency) else if pos < 0.5 color.new(color.from_gradient(pos, 0.333, 0.5, #FFFF00, #00FF00), transparency) else if pos < 0.666 color.new(color.from_gradient(pos, 0.5, 0.666, #00FF00, #00FFFF), transparency) else if pos < 0.833 color.new(color.from_gradient(pos, 0.666, 0.833, #00FFFF, #0000FF), transparency) else color.new(color.from_gradient(pos, 0.833, 1.0, #0000FF, #8B00FF), transparency) // Get color based on scheme and intensity getColor(bool isProfitable, float intensity, float maxIntensity, int bucketIdx) => float safeMax = maxIntensity > 0 ? maxIntensity : 1.0 float ratio = math.max(0.0, math.min(1.0, intensity / safeMax)) float positionRatio = bucketIdx / math.max(1.0, NUM_BUCKETS - 1.0) if COLOR_SCHEME == "Rainbow" getRainbowColor(positionRatio, ratio) else if COLOR_SCHEME == "Gradient" if isProfitable color.from_gradient(ratio, 0.0, 1.0, PROFIT_COLOR_DARK, PROFIT_COLOR_LIGHT) else color.from_gradient(ratio, 0.0, 1.0, LOSS_COLOR_DARK, LOSS_COLOR_LIGHT) else if COLOR_SCHEME == "Heatmap" color.from_gradient(ratio, 0.0, 1.0, #1a237e, #f44336) else if isProfitable color.new(#5d606b, int(math.round((1.0 - ratio) * 70))) else color.new(#e91e63, int(math.round((1.0 - ratio) * 70))) // Update method method update(PCD this) => int candleCount = array.size(this.candles) if candleCount > 0 and not na(this.priceStep) and this.priceStep > 0 // Create distribution array array dist = array.new_float(NUM_BUCKETS, 0.0) // Process each candle for candleIdx = 0 to candleCount - 1 Candle candle = array.get(this.candles, candleIdx) bool isFirstCandle = candleIdx == 0 float turnover = AUTO_TUNE ? calcAdaptiveTurnover(candle.atrPct, candle.relativeVol) : MANUAL_DECAY * candle.relativeVol turnover := math.min(turnover, 0.95) this.calculatedTurnover := turnover int startIdx = this.getBucketIndex(candle.lo) int endIdx = this.getBucketIndex(candle.hi) int buckets = math.max(1, endIdx - startIdx + 1) if isFirstCandle float initialWeight = 1.0 / buckets for i = startIdx to endIdx array.set(dist, i, initialWeight) else float decayedAmount = 0.0 for i = 0 to NUM_BUCKETS - 1 float oldVal = array.get(dist, i) float newVal = oldVal * (1.0 - turnover) array.set(dist, i, newVal) decayedAmount += oldVal - newVal float addPerBucket = decayedAmount / buckets for i = startIdx to endIdx array.set(dist, i, array.get(dist, i) + addPerBucket) // Normalize distribution float totalWeight = 0.0 for i = 0 to NUM_BUCKETS - 1 totalWeight += array.get(dist, i) if totalWeight > 0 for i = 0 to NUM_BUCKETS - 1 array.set(dist, i, array.get(dist, i) / totalWeight) // Find peak float maxWeight = array.max(dist) if na(maxWeight) or maxWeight <= 0 maxWeight := 0.001 int peakIndex = array.indexof(dist, maxWeight) if peakIndex < 0 peakIndex := 0 float peakPrice = this.getBucketedPrice(peakIndex) // Find support/resistance zones array srIndices = array.new(0) if SHOW_SUPPORT_RESISTANCE bool inZone = false int zoneStart = 0 for i = 0 to NUM_BUCKETS - 1 bool isHighConcentration = array.get(dist, i) >= maxWeight * SR_THRESHOLD if isHighConcentration and not inZone inZone := true zoneStart := i else if not isHighConcentration and inZone inZone := false array.push(srIndices, int(math.floor((zoneStart + i) / 2))) if inZone array.push(srIndices, int(math.floor((zoneStart + NUM_BUCKETS - 1) / 2))) // Clear old SR zones int srZoneSize = array.size(this.srZones) if srZoneSize > 0 for i = 0 to srZoneSize - 1 box b = array.get(this.srZones, i) box.set_lefttop(b, 0, 0) box.set_rightbottom(b, 0, 0) // Draw the distribution float lowestDisplayedPrice = na float highestDisplayedPrice = na for i = 0 to NUM_BUCKETS - 1 float weight = array.get(dist, i) float price = (i + 0.5) * this.priceStep + this.minPrice int width = int(math.round(weight / maxWeight * CHART_MAX_WIDTH)) line ln = array.get(this.lines, i) if width > 0 if na(lowestDisplayedPrice) lowestDisplayedPrice := price highestDisplayedPrice := price int x1 = bar_index + CHART_X_OFFSET int x2 = x1 - width bool isProfitable = price < close color c = getColor(isProfitable, weight, maxWeight, i) line.set_xy1(ln, x1, price) line.set_xy2(ln, x2, price) line.set_color(ln, c) else line.set_xy1(ln, 0, 0) line.set_xy2(ln, 0, 0) // Draw S/R zones if SHOW_SUPPORT_RESISTANCE int srCount = array.size(srIndices) int leftBar = math.max(0, bar_index - LOOKBACK) if srCount > 0 for i = 0 to srCount - 1 int idx = array.get(srIndices, i) float zonePrice = this.getBucketedPrice(idx) float zoneHalfHeight = this.priceStep * 3 box b = na if i < array.size(this.srZones) b := array.get(this.srZones, i) box.set_lefttop(b, leftBar, zonePrice + zoneHalfHeight) box.set_rightbottom(b, bar_index, zonePrice - zoneHalfHeight) else b := box.new(leftBar, zonePrice + zoneHalfHeight, bar_index, zonePrice - zoneHalfHeight, bgcolor = color.new(PEAK_COLOR, 85), border_color = color.new(PEAK_COLOR, 60)) array.push(this.srZones, b) // Calculate cumulative distribution array cumdist = array.copy(dist) for i = 1 to NUM_BUCKETS - 1 array.set(cumdist, i, array.get(cumdist, i - 1) + array.get(cumdist, i)) // Highlight current price int closeIndex = this.getBucketIndex(close) if closeIndex >= 0 and closeIndex < NUM_BUCKETS line.set_color(array.get(this.lines, closeIndex), CURRENT_PRICE_COLOR) // Calculate stats float totalShares = array.get(cumdist, NUM_BUCKETS - 1) int profitIndex = math.min(closeIndex + 1, NUM_BUCKETS - 1) float profitRatio = totalShares > 0 ? array.get(cumdist, profitIndex) / totalShares : 0.0 // Calculate average price float avg = 0.0 for i = 0 to NUM_BUCKETS - 1 float weight = array.get(dist, i) float price = this.getBucketedPrice(i) avg += price * weight int avgIndex = this.getBucketIndex(avg) if avgIndex >= 0 and avgIndex < NUM_BUCKETS line.set_color(array.get(this.lines, avgIndex), AVG_PRICE_COLOR) // Peak concentration - highlight line if SHOW_PEAK and peakIndex >= 0 and peakIndex < NUM_BUCKETS line.set_color(array.get(this.lines, peakIndex), PEAK_COLOR) // Smart label positioning - avoid overlaps float priceRange = na(highestDisplayedPrice) or na(lowestDisplayedPrice) ? close * 0.01 : (highestDisplayedPrice - lowestDisplayedPrice) float minLabelSpacing = priceRange * 0.025 // Sort prices and assign staggered X offsets float currentY = close float avgY = avg float peakY = peakPrice // Adjust avg label if too close to current if math.abs(avgY - currentY) < minLabelSpacing avgY := currentY > avgY ? avgY - minLabelSpacing : avgY + minLabelSpacing // Adjust peak label if too close to current or avg if SHOW_PEAK if math.abs(peakY - currentY) < minLabelSpacing peakY := currentY > peakY ? peakY - minLabelSpacing : peakY + minLabelSpacing if math.abs(peakY - avgY) < minLabelSpacing peakY := avgY > peakY ? peakY - minLabelSpacing : peakY + minLabelSpacing // Position price labels - compact format, right side of distribution label.set_text(this.currentPriceLabel, str.format('{0,number,#.##}', close)) label.set_xy(this.currentPriceLabel, bar_index + LABEL_X_OFFSET + 2, close) label.set_style(this.currentPriceLabel, label.style_label_left) label.set_size(this.currentPriceLabel, size.tiny) label.set_text(this.avgPriceLabel, str.format('{0,number,#.##} AVG', avg)) label.set_xy(this.avgPriceLabel, bar_index + LABEL_X_OFFSET + 2, avgY) label.set_style(this.avgPriceLabel, label.style_label_left) label.set_size(this.avgPriceLabel, size.tiny) if SHOW_PEAK label.set_text(this.peakLabel, str.format('{0,number,#.##} PEAK', peakPrice)) label.set_xy(this.peakLabel, bar_index + LABEL_X_OFFSET + 2, peakY) label.set_style(this.peakLabel, label.style_label_left) label.set_size(this.peakLabel, size.tiny) // Calculate ranges safely float safeTotalShares = totalShares > 0 ? totalShares : 1.0 int idx05 = array.binary_search_leftmost(cumdist, safeTotalShares * 0.05) int idx95 = array.binary_search_leftmost(cumdist, safeTotalShares * 0.95) int idx15 = array.binary_search_leftmost(cumdist, safeTotalShares * 0.15) int idx85 = array.binary_search_leftmost(cumdist, safeTotalShares * 0.85) float ninetyPctLow = this.getBucketedPrice(idx05) float ninetyPctHigh = this.getBucketedPrice(idx95) float seventyPctLow = this.getBucketedPrice(idx15) float seventyPctHigh = this.getBucketedPrice(idx85) float rangeDenom = ninetyPctHigh - ninetyPctLow float rangeOverlap = rangeDenom != 0 ? (seventyPctHigh - seventyPctLow) / rangeDenom : 0.0 // Calculate chip concentration float concentration = rangeOverlap * 100 string concentrationDesc = concentration < 50 ? "High" : concentration < 70 ? "Medium" : "Dispersed" // Pressure analysis float safeAvg = avg > 0 ? avg : close float priceVsAvg = ((close - safeAvg) / safeAvg) * 100 string pressure = priceVsAvg > 5 ? "Strong Bullish" : priceVsAvg > 1 ? "Bullish" : priceVsAvg < -5 ? "Strong Bearish" : priceVsAvg < -1 ? "Bearish" : "Neutral" // Price vs Peak float safePeak = peakPrice > 0 ? peakPrice : close float priceVsPeak = ((close - safePeak) / safePeak) * 100 string peakRelation = close > peakPrice ? "Above Peak" : close < peakPrice ? "Below Peak" : "At Peak" // Stats panel - positioned at bottom, compact float displayedRange = na(highestDisplayedPrice) or na(lowestDisplayedPrice) ? close * 0.02 : highestDisplayedPrice - lowestDisplayedPrice label.set_text(this.statsLabel, str.format( '90%: {0,number,#.##} - {1,number,#.##} | 70%: {2,number,#.##} - {3,number,#.##}', ninetyPctLow, ninetyPctHigh, seventyPctLow, seventyPctHigh)) if not na(lowestDisplayedPrice) and displayedRange > 0 label.set_y(this.statsLabel, lowestDisplayedPrice - displayedRange * 0.05) label.set_style(this.statsLabel, label.style_label_up) label.set_x(this.statsLabel, bar_index + CHART_X_OFFSET - 30) label.set_size(this.statsLabel, size.tiny) // Signal panel - hidden (info moved to trend arrow and pressure bar) label.set_text(this.signalLabel, "") label.set_xy(this.signalLabel, bar_index, close) // === NEW PROFESSIONAL VISUALIZATIONS === // 1. Key Level Lines - Support, Resistance, and Average Cost extending across chart if SHOW_KEY_LEVELS int chartLeft = math.max(0, bar_index - LOOKBACK) int chartRight = bar_index + CHART_X_OFFSET - 5 // Average cost line (horizontal dotted blue line) line.set_xy1(this.avgCostLine, chartLeft, avg) line.set_xy2(this.avgCostLine, chartRight, avg) line.set_color(this.avgCostLine, AVG_PRICE_COLOR) // Find strongest support (highest concentration below current price) float strongestSupport = na float strongestSupportWeight = 0.0 float strongestResistance = na float strongestResistanceWeight = 0.0 for i = 0 to NUM_BUCKETS - 1 float bucketPrice = this.getBucketedPrice(i) float bucketWeight = array.get(dist, i) if bucketPrice < close and bucketWeight > strongestSupportWeight strongestSupport := bucketPrice strongestSupportWeight := bucketWeight if bucketPrice > close and bucketWeight > strongestResistanceWeight strongestResistance := bucketPrice strongestResistanceWeight := bucketWeight // Support line (green dashed) if not na(strongestSupport) line.set_xy1(this.supportLine, chartLeft, strongestSupport) line.set_xy2(this.supportLine, chartRight, strongestSupport) line.set_color(this.supportLine, SUPPORT_COLOR) else line.set_xy1(this.supportLine, bar_index, close) line.set_xy2(this.supportLine, bar_index, close) line.set_color(this.supportLine, color.new(SUPPORT_COLOR, 100)) // Resistance line (red dashed) if not na(strongestResistance) line.set_xy1(this.resistanceLine, chartLeft, strongestResistance) line.set_xy2(this.resistanceLine, chartRight, strongestResistance) line.set_color(this.resistanceLine, RESISTANCE_COLOR) else line.set_xy1(this.resistanceLine, bar_index, close) line.set_xy2(this.resistanceLine, bar_index, close) line.set_color(this.resistanceLine, color.new(RESISTANCE_COLOR, 100)) // 2. Trend Direction Arrow if SHOW_TREND_ARROW string trendSymbol = priceVsAvg > 5 ? "▲▲" : priceVsAvg > 1 ? "▲" : priceVsAvg < -5 ? "▼▼" : priceVsAvg < -1 ? "▼" : "◆" color trendColor = priceVsAvg > 5 ? color.new(#00E676, 0) : priceVsAvg > 1 ? color.new(#4CAF50, 0) : priceVsAvg < -5 ? color.new(#FF1744, 0) : priceVsAvg < -1 ? color.new(#EF5350, 0) : color.new(#9E9E9E, 0) string trendText = trendSymbol + " " + pressure label.set_text(this.trendArrow, trendText) float arrowY = na(highestDisplayedPrice) ? close : highestDisplayedPrice + displayedRange * 0.12 label.set_xy(this.trendArrow, bar_index + CHART_X_OFFSET - 40, arrowY) label.set_color(this.trendArrow, color.new(trendColor, 70)) label.set_textcolor(this.trendArrow, trendColor) label.set_size(this.trendArrow, size.large) // 3. Pressure Bar (Profit/Loss ratio visualization) if SHOW_PRESSURE_BAR float barWidth = 8.0 float barHeight = displayedRange * 0.25 float barX = bar_index + CHART_X_OFFSET + 5 float barTop = na(highestDisplayedPrice) ? close + barHeight/2 : highestDisplayedPrice - displayedRange * 0.02 float barBottom = barTop - barHeight // Background bar box.set_lefttop(this.pressureBar, int(barX), barTop) box.set_rightbottom(this.pressureBar, int(barX + barWidth), barBottom) box.set_bgcolor(this.pressureBar, color.new(#424242, 60)) // Fill based on profit ratio (green from bottom) float fillHeight = barHeight * profitRatio float fillTop = barBottom + fillHeight color fillColor = profitRatio > 0.7 ? color.new(#00E676, 30) : profitRatio > 0.5 ? color.new(#4CAF50, 30) : profitRatio > 0.3 ? color.new(#FFC107, 30) : color.new(#FF5252, 30) box.set_lefttop(this.pressureFill, int(barX), fillTop) box.set_rightbottom(this.pressureFill, int(barX + barWidth), barBottom) box.set_bgcolor(this.pressureFill, fillColor) // Pressure label string pressureText = str.format('{0,number,#}%', profitRatio * 100) label.set_text(this.pressureLabel, pressureText) label.set_xy(this.pressureLabel, int(barX - 1), barTop + displayedRange * 0.01) label.set_textcolor(this.pressureLabel, fillColor) //#endregion //#region Main = request.security(syminfo.tickerid, 'D', , lookahead = barmerge.lookahead_off) float atrPercent = dailyClose > 0 ? dailyATR / dailyClose : 0.02 if timeframe.in_seconds(timeframe.period) <= timeframe.in_seconds('D') var PCD pcd = newPCD() if last_bar_index - bar_index < LOOKBACK pcd.storeCandle(dailyBarIdx, dailyHigh, dailyLow, dailyVolume, avgVolume, atrPercent) if barstate.islast pcd.update() //#endregion
Pine Script®指標
由billy10384提供
Neeson bitcoin Dynamic ATR Trailing SystemNeeson bitcoin Dynamic ATR Trailing System: A Comprehensive Guide to Volatility-Adaptive Trend Following Introduction The Dynamic ATR Trailing System (DATR-TS) represents a sophisticated approach to trend following that transcends conventional moving average or breakout-based methodologies. Unlike standard trend-following systems that rely on price pattern recognition or fixed parameter oscillators, this system operates on the principle of volatility-adjusted position management—a nuanced approach that dynamically adapts to changing market conditions rather than imposing rigid rules on market behavior. Originality and Innovation Distinct Methodological Approach What sets DATR-TS apart from hundreds of existing trend-following systems is its dual-layered conditional execution framework. While most trend-following systems fall into one of three broad categories—moving average crossovers, channel breakouts, or momentum oscillators—this system belongs to the more specialized category of volatility-normalized trailing stop systems. Key Original Contributions: Volatility-Threshold Signal Filtering: Most trend systems generate signals continuously, leading to overtrading during low-volatility periods. DATR-TS implements a proprietary volatility filter that requires minimum market movement before generating signals, effectively separating high-probatility trend opportunities from market noise. Self-Contained Position State Management: Unlike traditional systems that require external position tracking, DATR-TS maintains an internal position state that prevents contradictory signals and creates a closed-loop decision framework. Dynamic Risk Parameter Adjustment: The system doesn't use fixed percentage stops or rigid ATR multiples. Instead, it implements a responsive adjustment mechanism that widens stops during high volatility and tightens them during low volatility, creating an optimal balance between risk protection and opportunity capture. Trader-Centric Visualization Philosophy: Beyond mere signal generation, the system provides a comprehensive visual feedback system designed to align with human cognitive patterns, reducing emotional decision-making through consistent color coding and information hierarchy. Technical Implementation and Functionality Core Operational Mechanism DATR-TS implements a volatility-adjusted trend persistence model that operates on the principle that trending markets exhibit characteristic volatility signatures. The system specifically targets medium-term directional movements (typically lasting 5-20 days) rather than short-term scalping opportunities or long-term position trades. The Four-Pillar Architecture: Volatility Measurement and Normalization Calculates Average True Range (ATR) over a user-defined period Converts absolute volatility to percentage terms relative to price Compares current volatility against user-defined thresholds to filter suboptimal conditions Dynamic Trailing Stop Algorithm Establishes an initial stop distance based on current volatility Implements a four-state adjustment mechanism that responds to price action Maintains stop position during trend continuation while allowing for trend reversal detection Conditional Signal Generation Generates entry signals only when price action meets both directional and volatility criteria Produces exit signals based on trailing stop penetration Incorporates position state awareness to prevent conflicting signals Comprehensive Feedback System Provides multi-layer visual information including dynamic stop lines, signal labels, and color-coded price action Displays real-time metrics through an integrated dashboard Offers configurable visualization options for different trading styles Specific Trend-Following Methodology DATR-TS employs a volatility-normalized trailing stop breakout approach, which differs significantly from common trend identification methods: Not a moving average crossover system (like MACD or traditional MA crosses) Not a channel breakout system (like Bollinger Band or Donchian Channel breaks) Not a momentum oscillator system (like RSI or Stochastic trend following) Not a price pattern recognition system (like head-and-shoulders or triangle breaks) Instead, it belongs to the more specialized category of volatility-adjusted stop-and-reverse systems that: Wait for market volatility to reach actionable levels Establish positions when price confirms directional bias through stop penetration Manage risk dynamically based on evolving market conditions Exit positions when the trend exhausts itself through stop violation Practical Application and Usage Market Environment Optimization Ideal Conditions: Trending markets with sustained directional movement Medium volatility environments (neither excessively calm nor chaotic) Timeframes: 4-hour to daily charts for optimal signal quality Instruments: Forex majors, commodity futures, equity indices Suboptimal Conditions: Ranging or consolidating markets Extreme volatility events or news-driven spikes Very short timeframes (below 1-hour) Illiquid or highly manipulated instruments Parameter Configuration Strategy Core Parameter Philosophy: ATR Length (Default: 21 periods) Controls the system's memory of volatility Shorter lengths increase sensitivity but may cause overtrading Longer lengths provide smoother signals but may lag during volatility shifts ATR Multiplier (Default: 6.3x) Determines the initial risk buffer Lower values (4-5x) create tighter stops for conservative trading Higher values (6-8x) allow for larger trends but increase drawdown risk Volatility Threshold (Default: 1.5%) Filters out low-quality trading environments Adjust based on market characteristics (higher for volatile markets) Acts as a quality control mechanism for signals Trading Workflow and Execution Signal Interpretation and Action: Entry Protocol: Wait for BLUE "BUY" signal label appearance Confirm volatility conditions meet threshold requirements Enter long position at market or next reasonable opportunity Set initial stop at displayed dynamic stop level Position Management: Monitor dynamic stop line for position adjustment Allow profits to run while stop protects capital No manual adjustment required—system manages stop automatically Exit Protocol: Exit on ORANGE "SELL" signal label appearance Alternative exit if price hits dynamic stop level System will generate new entry signal if conditions warrant re-entry Risk Management Integration: Position sizing based on distance to dynamic stop Volatility filter prevents trades during unfavorable conditions Clear visual feedback on current risk exposure Built-in protection against overtrading Philosophical Foundation and Market Theory Core Trading Principles DATR-TS embodies several foundational market principles: Volatility Defines Opportunity Markets don't trend continuously—they alternate between trending and ranging phases Volatility provides the energy for trends to develop and sustain By measuring and filtering volatility, we can focus on high-probability trend phases Risk Should Be Proportional Fixed percentage stops ignore market context Dynamic stops that adjust with volatility provide more appropriate risk management Position sizing should reflect current market conditions, not arbitrary rules Simplicity Through Sophistication Complex systems often fail in real-world conditions A simple core algorithm with intelligent filtering outperforms complex multi-indicator approaches Clear visual feedback reduces cognitive load and emotional interference Trends Persist Until Proven Otherwise Markets exhibit momentum characteristics Once a trend establishes itself, it tends to continue The trailing stop methodology captures this persistence while providing exit mechanisms Mathematical and Statistical Foundation The system operates on several statistical market observations: Volatility Clustering Phenomenon High volatility periods tend to follow high volatility periods Low volatility periods tend to follow low volatility periods By filtering for adequate volatility, we increase the probability of capturing meaningful trends Trend Magnitude Distribution Most trends are small to medium in magnitude Very large trends are rare but account for disproportionate returns The dynamic stop methodology allows capture of varying trend magnitudes Autocorrelation in Price Movements Price movements exhibit short-term positive autocorrelation during trends This persistence allows trailing stops to capture continued movement The system leverages this characteristic without requiring explicit autocorrelation calculation Performance Characteristics and Expectations Typical System Behavior Signal Frequency: Low to moderate signal generation (prevents overtrading) Signals concentrated during trending market phases Extended periods without signals during ranging conditions Risk-Reward Profile: Win rate typically 40-60% in trending conditions Average win larger than average loss Risk-reward ratios of 1:2 to 1:3 achievable Drawdown Patterns: Controlled through volatility adjustment Larger drawdowns during extended ranging periods Recovery typically follows when trending conditions resume Comparison with Alternative Approaches Versus Moving Average Systems: Less prone to whipsaws during ranging markets Better adaptation to changing volatility conditions Clearer exit signals through stop levels Versus Channel Breakout Systems: More responsive to emerging trends Lower false breakout probability Dynamic risk adjustment rather than fixed parameters Versus Momentum Oscillator Systems: Better trend persistence capture Less susceptible to overbought/oversold false signals Clearer position management rules Educational Value and Skill Development Learning Opportunities DATR-TS serves as more than just a trading tool—it provides educational value through: Market Condition Awareness Teaches traders to distinguish between trending and ranging markets Develops understanding of volatility's role in trading opportunities Encourages patience and selectivity in trade execution Risk Management Discipline Demonstrates dynamic position sizing principles Illustrates the importance of adaptive stops Reinforces the concept of risk-adjusted returns Psychological Skill Development Reduces emotional trading through clear rules Builds patience through conditional execution Develops discipline through systematic approach Customization and Evolution The system provides a foundation for further development: Beginner Level: Use default parameters for initial learning Focus on signal recognition and execution discipline Develop understanding of system behavior across market conditions Intermediate Level: Adjust parameters based on specific market characteristics Combine with complementary analysis techniques Develop personal variations based on trading style Advanced Level: Integrate with portfolio management systems Develop automated execution frameworks Create derivative systems for specialized applications Conclusion: The Modern Trend-Following Paradigm The Dynamic ATR Trailing System represents a significant evolution in trend-following methodology. By moving beyond simple price pattern recognition or fixed parameter oscillators, it embraces the complex reality of financial markets where volatility, trend persistence, and risk management interact dynamically. This system doesn't claim to predict market direction or identify tops and bottoms. Instead, it provides a systematic framework for participating in trends when they emerge, managing risk appropriately as conditions change, and preserving capital during unfavorable environments. For traders seeking a methodology that combines mathematical rigor with practical execution, adapts to changing market conditions rather than fighting against them, and provides clear, actionable information without cognitive overload, DATR-TS offers a sophisticated yet accessible approach to modern trend following. The true value lies not in any single signal or parameter setting, but in the comprehensive philosophy of volatility-aware, risk-adjusted, conditionally-executed trend participation that the system embodies—a philosophy that aligns with how markets actually behave rather than how we might wish them to behave.
Pine Script®指標
由neeson1987提供
OHLC+ Pre Market + ORB + 9 21 200 EMAs + VWAPOHLC Suite - Complete Price Level & Technical Indicator Package This all-in-one indicator provides essential price levels and technical indicators for intraday trading, combining multiple reference points in a single, customizable overlay. Features: 📊 Previous Day's OHLC Open, High, Low, and Close levels from the previous trading day Helps identify key support/resistance levels and reference points Customizable line styles (Solid/Dashed/Dotted) and colors 📈 Today's OHLC Current day's Open, High, Low, and Close levels Real-time updates as price action develops Separate styling options from previous day levels 🌅 Premarket High/Low Tracks high and low during premarket hours (4:00 AM - 9:30 AM ET) Essential for gap trading and identifying early morning range Displays after regular session opens ⚡ Opening Range Breakout (ORB) Calculates high/low of first 15 minutes (9:30 AM - 9:45 AM ET) Popular for momentum and breakout strategies Shows range boundaries after initial period 📉 Exponential Moving Averages (EMAs) EMA 9 (short-term trend) EMA 21 (intermediate trend) EMA 200 (long-term trend/major support-resistance) Toggle each EMA independently 📊 Volume Weighted Average Price (VWAP) Standard VWAP calculation using hlc3 Key institutional reference level Useful for mean reversion and trend following Customization Options: Individual color and opacity controls for all elements Show/hide any component independently Adjustable line styles for different level types Price labels with abbreviations or actual values Clean, organized settings interface Best For: Day traders and swing traders Multi-timeframe analysis Support/resistance identification Breakout and range trading strategies Institutional level awareness Settings: All colors, transparencies, line styles, and visibility options are fully customizable through the indicator settings panel. Default configuration provides optimal visibility with distinct colors for different level types.
Pine Script®指標
由pranayraj09提供
CVD-MACD### CVD-MACD (Research) The CVD-MACD is a research-oriented indicator that combines Cumulative Volume Delta (CVD) with the classic MACD framework to provide insights into market momentum and potential reversals. Unlike a standard MACD based on price, this version uses CVD (the running total of buy vs. sell volume delta) as its input source, offering a volume-driven perspective on trend strength and divergences. Key Features: - **CVD-Based MACD Calculation**: Computes MACD using CVD instead of price, highlighting volume imbalances that may precede price moves. - **Dual Divergence Detection**: Identifies bullish/bearish divergences on both the MACD line and histogram, with configurable pivot lookbacks and filters (e.g., momentum decay and zero-side consistency). - **Visual Flexibility**: Toggle divergences in the indicator pane or overlaid on the main chart, with optional raw CVD line for reference. - **Alerts**: Built-in conditions for bullish and bearish divergences to notify users of potential setups. ###This indicator is designed for research and experimentation—it's not financial advice. It performs best on liquid assets with reliable volume data (e.g., stocks, futures). I've shared this to gather community feedback: please test it thoroughly and point out any bugs, inefficiencies, or improvements! For example, if you spot issues with divergence detection on certain timeframes or symbols, let me know in the comments. Your input will help refine it. Inspired by volume analysis techniques; open to collaborations or forks. ## User Manual for CVD-MACD (Research) ### Overview The CVD-MACD indicator transforms traditional MACD by using Cumulative Volume Delta (CVD) as the base input. CVD accumulates the net delta between estimated buy and sell volume per bar, providing a volume-centric view of momentum. The indicator plots a MACD line, signal line, and histogram, while also detecting divergences on both the MACD line and histogram for potential reversal signals. This manual covers setup, interpretation, and troubleshooting. Note: This is a research tool—backtest and validate on your own data before using in live trading. ### Installation and Setup 1. **Add to Chart**: Search for "CVD-MACD (Research)" in TradingView's indicator library or paste the script into the Pine Editor and add it to your chart. 2. **Compatibility**: Works on any timeframe and symbol with volume data. Best on daily/intraday charts for stocks, forex, or futures. Avoid illiquid symbols where volume may be unreliable. 3. **Customization**: All inputs are configurable via the indicator's settings panel. Defaults are optimized for general use but can be tuned based on asset volatility. ### Input Parameters The inputs are grouped for ease of use: #### MACD Settings - **Fast EMA (CVD)** (default: 12): Length of the fast EMA applied to CVD. Shorter values make it more responsive to recent volume changes. - **Slow EMA (CVD)** (default: 26): Length of the slow EMA on CVD. Longer values smooth out noise for trend identification. - **Signal EMA** (default: 9): Smoothing period for the signal line (EMA of the MACD line). #### Divergence Logic (MACD Line) - **Pivot Lookback (MACD Line)** (default: 5): Bars to look left/right for detecting pivots on the MACD line. Higher values detect larger swings but may miss smaller divergences. - **Max Lookback Range (MACD Line)** (default: 50): Maximum bars between two pivots to consider a divergence valid. Prevents detecting outdated signals. - **Enable Momentum Decay Filter (Histogram)** (default: false): When enabled, requires the histogram to show decaying momentum (absolute value decreasing) for MACD-line divergences to trigger. #### Histogram Divergence - **Pivot Lookback (Histogram)** (default: 5): Similar to above, but for histogram pivots. - **Max Lookback Range (Histogram)** (default: 50): Max bars for histogram divergence detection. - **Show Histogram Divergences in Indicator Pane** (default: true): Displays dashed lines and "H" labels for histogram divergences in the sub-window. - **Show Histogram Divergences on Main Chart** (default: true): Overlays histogram divergences on the price chart with semi-transparent lines and labels. - **Require Histogram to Stay on Same Side of Zero** (default: true): Filters divergences to only those where the histogram doesn't cross zero between pivots, ensuring consistent momentum direction. #### Visuals (Dual View) - **Show MACD-Line Divergences (Indicator Pane)** (default: true): Draws solid lines and "L" labels for MACD-line divergences in the sub-window. - **Show MACD-Line Divergences (Main Chart)** (default: true): Overlays MACD-line divergences on the price chart. - **Show Raw CVD Line** (default: false): Plots the underlying CVD as a faint gray line for reference. ### How to Interpret the Indicator 1. **Core Plots**: - **MACD Line** (blue): Difference between fast and slow CVD EMAs. Above zero indicates building buy volume momentum; below zero shows sell dominance. - **Signal Line** (orange): EMA of the MACD line. Crossovers can signal potential entries/exits (e.g., MACD above signal = bullish). - **Histogram** (columns): MACD minus signal. Green shades for positive/expanding bars (bullish momentum); red for negative/contracting (bearish). Fading colors indicate weakening momentum. - **Zero Line** (gray horizontal): Reference for bullish (above) vs. bearish (below) territory. - **Raw CVD** (optional gray line): The cumulative buy-sell delta. Rising = net buying; falling = net selling. 2. **Divergences**: - **Bullish (Green Lines/Labels)**: Occur when price makes lower lows, but MACD line or histogram makes higher lows. Suggests weakening downside momentum and potential reversal up. Look for "L" (MACD line) or "H" (histogram) labels. - **Bearish (Red Lines/Labels)**: Price higher highs vs. MACD/histogram lower highs. Indicates fading upside and possible downturn. - **Dual View**: Divergences appear in the indicator pane (sub-window) for clean analysis and overlaid on the main chart for price context. Histogram divergences use dashed lines to distinguish from MACD-line (solid). - **Filters**: Momentum decay ensures only "hidden" or weakening divergences trigger. Zero-side filter prevents false signals from oscillating histograms. 3. **Alerts**: - **Bullish Divergence (L or H)**: Triggers on either MACD-line or histogram bullish divergence. Message: "CVD-MACD Bullish Divergence detected on {{ticker}}". - **Bearish Divergence (L or H)**: Similar for bearish. Use TradingView's alert setup to notify via email/SMS/webhook. - Tip: Combine with price action (e.g., support/resistance) for confirmation. ### Usage Tips and Strategies - **Trend Confirmation**: Use in uptrends for bullish divergences (pullback buys) or downtrends for bearish (short entries). - **Timeframe Selection**: Higher timeframes (e.g., daily) for swing trading; lower (e.g., 15-min) for intraday. Adjust pivot lookbacks accordingly (shorter for faster charts). - **Combination Ideas**: Pair with RSI for overbought/oversold confirmation or VWAP for intraday volume context. - **Risk Management**: Divergences are probabilistic—not guarantees. Always use stop-losses based on recent swings. - **Performance Notes**: Backtest on historical data via TradingView's Strategy Tester. CVD relies on accurate volume; test on exchanges like NYSE/NASDAQ. ### Known Limitations and Troubleshooting - **Volume Dependency**: CVD estimation assumes linear buy/sell distribution based on bar position—may be less accurate on thin markets or during gaps. - **Repainting**: Pivots and divergences can repaint as new data arrives (common in pivot-based indicators). Use on closed bars for reliability. - **Resource Usage**: High max_bars_back (5000) ensures deep history; reduce if chart loads slowly. - **No Signals on Low-Volume Bars**: If CVD flatlines, check symbol volume—some crypto/forex pairs have inconsistent data. - **Community Feedback**: If you encounter bugs (e.g., false divergences on specific symbols/timeframes), missing alerts, or calculation errors, please comment below with details like symbol, timeframe, and screenshots. Suggestions for enhancements (e.g., more filters or visuals) are welcome! If you have questions or find issues, drop a comment—let's improve this together!
Pine Script®指標
由Kuokkuok0503提供
Manual Backtest Dashboard (100 Trades)Manual Backtest Dashboard (100 Trades) is a lightweight TradingView indicator designed to help traders manually record and evaluate their trading performance directly on the chart. This tool is built specifically for discretionary traders such as SMC, price action, scalping, and intraday traders who want to analyze their win rate and overall performance without relying on the Strategy Tester. The indicator works by allowing users to input their trade results manually through the settings panel. Each trade is recorded using simple values: 1 for a winning trade, -1 for a losing trade, and 0 for an empty or uncounted trade. The dashboard automatically calculates the total number of trades entered, the number of wins and losses, and the win rate percentage in real time. Users do not need to fill all 100 trade slots, as only trades with non-zero values are included in the calculations. This indicator does not place trades or generate buy and sell signals. Instead, it focuses purely on performance evaluation, making it ideal for subjective backtesting, forward testing, and manual trading journals. The dashboard is clean, lightweight, and does not clutter the price chart, ensuring a smooth and distraction-free trading experience. The script is stable, efficient, and does not repaint, making it a reliable tool for traders who want to track and improve their consistency over time.
Pine Script®指標
由arlentraalley提供
MTT Cyclical vs Defensive Z-ScoreThe MTT Cyclical vs Defensive Z-Score is a sophisticated sentiment and rotation indicator designed to measure the relative strength of "risk-on" sectors against "risk-off" havens. It calculates a ratio between two distinct baskets: Cyclicals (Consumer Discretionary, Industrials, Materials) and Defensives/Commodities (Consumer Staples, Health Care, Utilities, and the DBC Commodity Index). By applying a Z-score calculation to this ratio, the indicator identifies how many standard deviations the current market leadership is away from its mean. This transforms a simple ratio into a powerful tool for identifying market extremes and potential pivot points. How the Indicator Works The script follows a logical three-step process to quantify market sentiment: Basket Comparison: It pits growth-sensitive sectors (which thrive during economic expansion) against defensive sectors and commodities (which act as anchors or inflation hedges). Mean Reversion: It uses a Simple Moving Average (SMA) and Standard Deviation over a 20-period lookback to determine the "normal" range for this relationship. Standardization: The resulting Z-score oscillates around a zero line. Green columns represent periods where cyclicals are outperforming their recent average, while red columns indicate defensive leadership. How to Use It for Trading The Z-score serves as a barometer for overextended market moves: Identifying Extreme Optimism: When the Z-score crosses above +2.0, cyclicals are significantly overextended. This suggests the "risk-on" move may be exhausted, signaling a potential pullback or a rotation back into defensive stocks. Identifying Extreme Fear: When the Z-score drops below -2.0, defensives and commodities are heavily favored. This often coincides with market bottoms or "washouts," suggesting that a bounce in cyclical sectors (and the broader market) may be imminent. Trend Confirmation: Crossing the 0.0 (Mean) line acts as a momentum shifter. Moving from negative to positive suggests a fresh bullish rotation is gaining traction.
Pine Script®指標
由mad_tom_trading提供